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The Saarbrücken Graduate School of Computer Science provides an optimal environment for pursuing doctoral studies in computer science at an internationally competitive level. As a student, you
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‑space exploration, and on‑line operational optimization of power systems. Your tasks in detail: Become familiar with our previously developed neural network superstructure for learning iterative
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to accelerate solving AC power flow (AC-PF) computations, potentially facilitating real‑time contingency analysis, rapid design‑space exploration, and on‑line operational optimization of power systems
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prediction Integration of domain decomposition methods into the learning framework to enable efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation
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efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation of models on patient-specific geometries obtained from MRI data Participation in conferences
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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic
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(including data science courses, soft skill courses and annual retreats): https://www.hds-lee.de/about/ A qualification that is highly valued in industry 30 days of annual leave and flexible working
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data sets, which have to be evaluated in order to obtain a holistic understanding of very complex systems. Visit HDS-LEE at: https://www.hds-lee.de/ The position is placed at the Institute for Advanced
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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop 3D+t image reconstruction methods in a cell microscopy setting using image sequences as well as focus stacks
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retreats) https://www.hds-lee.de/about/ A qualification that is highly welcome in industry 30 days of annual leave and flexible working arrangements, including partial remote work Further development of your